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Churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics
While advances in genome sequencing technology make population-scale genomics a possibility, current approaches for analysis of these data rely upon parallelization strategies that have limited scalability, complex implementation and lack reproducibility. Churchill, a balanced regional parallelizati...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4333267/ https://www.ncbi.nlm.nih.gov/pubmed/25600152 http://dx.doi.org/10.1186/s13059-014-0577-x |
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author | Kelly, Benjamin J Fitch, James R Hu, Yangqiu Corsmeier, Donald J Zhong, Huachun Wetzel, Amy N Nordquist, Russell D Newsom, David L White, Peter |
author_facet | Kelly, Benjamin J Fitch, James R Hu, Yangqiu Corsmeier, Donald J Zhong, Huachun Wetzel, Amy N Nordquist, Russell D Newsom, David L White, Peter |
author_sort | Kelly, Benjamin J |
collection | PubMed |
description | While advances in genome sequencing technology make population-scale genomics a possibility, current approaches for analysis of these data rely upon parallelization strategies that have limited scalability, complex implementation and lack reproducibility. Churchill, a balanced regional parallelization strategy, overcomes these challenges, fully automating the multiple steps required to go from raw sequencing reads to variant discovery. Through implementation of novel deterministic parallelization techniques, Churchill allows computationally efficient analysis of a high-depth whole genome sample in less than two hours. The method is highly scalable, enabling full analysis of the 1000 Genomes raw sequence dataset in a week using cloud resources. http://churchill.nchri.org/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-014-0577-x) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4333267 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43332672015-02-20 Churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics Kelly, Benjamin J Fitch, James R Hu, Yangqiu Corsmeier, Donald J Zhong, Huachun Wetzel, Amy N Nordquist, Russell D Newsom, David L White, Peter Genome Biol Method While advances in genome sequencing technology make population-scale genomics a possibility, current approaches for analysis of these data rely upon parallelization strategies that have limited scalability, complex implementation and lack reproducibility. Churchill, a balanced regional parallelization strategy, overcomes these challenges, fully automating the multiple steps required to go from raw sequencing reads to variant discovery. Through implementation of novel deterministic parallelization techniques, Churchill allows computationally efficient analysis of a high-depth whole genome sample in less than two hours. The method is highly scalable, enabling full analysis of the 1000 Genomes raw sequence dataset in a week using cloud resources. http://churchill.nchri.org/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-014-0577-x) contains supplementary material, which is available to authorized users. BioMed Central 2015-01-20 2015 /pmc/articles/PMC4333267/ /pubmed/25600152 http://dx.doi.org/10.1186/s13059-014-0577-x Text en © Kelly et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Method Kelly, Benjamin J Fitch, James R Hu, Yangqiu Corsmeier, Donald J Zhong, Huachun Wetzel, Amy N Nordquist, Russell D Newsom, David L White, Peter Churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics |
title | Churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics |
title_full | Churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics |
title_fullStr | Churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics |
title_full_unstemmed | Churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics |
title_short | Churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics |
title_sort | churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4333267/ https://www.ncbi.nlm.nih.gov/pubmed/25600152 http://dx.doi.org/10.1186/s13059-014-0577-x |
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